The SICAS Medical Image Repository

The SICAS Medical Image Repository is the place for you to store medical research data.

ISLES 2017 CHALLENGE

The ISLES challenge is a medical image segmentation challenge with the aim to compare different methods for ischemic stroke lesion segmentation from multi-spectral MRI images. ISLES is part of MICCAI 2017 conference!

Brain Tumor Image Segmentation Challenge

Segmentation of brain tumors is a critical step in treatment planning and evaluation of response to therapy. It is also one of the most challenging tasks in medical image analysis, due to the variable shape and heterogeneity of such tumors. Multicenter data will be used for segmentation of four tumor subregions, while inter-reader agreement from clinicians will be used as a benchmark for comparing the algorithm.

mTOP 2016

Welcome to the Mild Traumatic Brain Injury Outcome Prediction (mTOP) challenge. Its aim is to create a common ground to compare methods to find predictive MRI features, which help to characterise and distinguish mild traumatic brain injury patients from each other and healthy subjects.

SHAPE 2015 Challenge

Obtain a set of 47 training liver data as binary images and a set of 10 triangle meshes of partial liver shapes. The goal of the challenge is to obtain the best possible reconstruction (shape completion) for the 10 given partial livers.

Visceral.eu Anatomy Benchmark

The Benchmark tasks will be organ identification and the segmentation of bones, inner organ and relevant substructures. The VSD-SMIR is hosting the benchmark data.

Computational Horizons In Cancer (CHIC)

Developing Meta- and Hyper-Multiscale Models and Repositories for In Silico Oncology: After passing through the de-identification and (pseudo)-anonymization processes all the relevant medical data including imaging, clinical, histological and gentetic data for each patient will be hosted by the clinical data repository.

Offers a joint publisher-curated list of appropriate data deposition repositories in the field of life sciences

Our Competences

Storing medical image data requires special knowledge. SICAS offers a unique combination of competence in acquiring and storing medical images, in processing and visualising data for research and applications in medicine.

Anonymisation

Anonymisation of patient information and image features like face soft tissue.

Data Storage

Certified, efficient, and innovative data center based in Switzerland.

Research expertise

Sound expertise and broad experience in research support and collaboration management.